New research shows that access to AI is not the same as knowing where to use it.
A firm is only as fast as the slowest step in its chain of work. In manufacturing, it might be one particular machine on the line. In software, one overloaded intake service. Many business leaders are accidentally recreating this scenario with artificial intelligence. They provision AI tools to employees and hear about localized productivity spikes, but the company鈥檚 overall performance barely moves. This tension lies at the heart of the new working paper 鈥�,鈥� from co-authors at INSEAD and the Digital Data Design Institute at 性视界 (D^3). By tracking hundreds of organizations, the researchers have uncovered friction points that hold firms back from realizing the true economic promise of generative AI.
Why This Matters
For business leaders and executives, this research shows that the organizations most likely to realize substantial AI-driven results are those that invest not just in technology, but in the wide-ranging process of exploring where it fits. That is a strategy and execution problem, and leaders will need to ask which parts of their organizations need redesign rather than optimization. If you don鈥檛 actively push the boundaries of how AI rewrites your firm, you risk using a map that never leads you to your destination.
Link to the D^3 insight article
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